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   "source": [
    "# Bivariate Plot of Penguin Measurements\n",
    "\n",
    "This example shows how to visualize the joint distribution of two numerical features using a bivariate plot. Here, we explore the relationship between bill length and flipper length in the Penguins dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae296edc-9c65-4c40-b899-8317ec2c294d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import hvplot.pandas  # noqa\n",
    "\n",
    "df = hvplot.sampledata.penguins(\"pandas\")\n",
    "\n",
    "df.hvplot.bivariate(x=\"bill_length_mm\", y=\"flipper_length_mm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d1efb187-48ad-428d-b9ea-698f453c62e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import hvplot.pandas  # noqa\n",
    "hvplot.extension(\"matplotlib\")\n",
    "\n",
    "df = hvplot.sampledata.penguins(\"pandas\")\n",
    "\n",
    "df.hvplot.bivariate(x=\"bill_length_mm\", y=\"flipper_length_mm\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48036436-cf26-4c80-944f-e1baaaf216d4",
   "metadata": {},
   "source": [
    ":::{seealso}\n",
    "- [Bivariate plots reference documentation](../../ref/api/manual/hvplot.hvPlot.bivariate.ipynb).\n",
    ":::"
   ]
  }
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